Senior Manager – Data Scientist
Tasks
- Conduct cost/benefit analysis
- Conduct executive updates
- Create solution roadmaps
- Design multi-agent systems
- Ensure best practices
- Explore emerging AI trends for HR use cases
- Identify HR business problems
- Implement machine learning solutions
- Lead data science and AI engineering team
- Lead end to end AI deployment
- Lead solution design for RAG pipelines
- Manage cloud deployment on Azure AWS
- Orchestrate LLM workflows
- Oversee solution testing and deployment
- Perform architecture reviews
- Perform code reviews
- Present executive recommendations
- Prioritize AI use cases
- Translate business requirements into technical specs
Perks/Benefits
- N/A
Skills/Tech-stack
AWS SageMaker | Agent systems | Azure Machine Learning | BERT | Chain-of-Thought | Cloud Computing | Clustering | Convolutional Neural Networks | Deep learning | Fine Tuning | GCP Vertex | GCP Vertex AI | Keras | LLM Evaluation | Language Models | Language Processing | Large Language Models | LoRA | Logistic Regression | Long Short-Term Memory | MLOps | Machine Learning | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | Neural Networks | PEFT | Pandas | Prompt engineering | PyTorch | Python | RAG | Random Forest | React | Recurrent Neural Networks | Retrieval-Augmented Generation | SQL | Scikit-learn | Short Term Memory | Spark | Support Vector Machines | TensorFlow | Transformers | Vector machines | Vertex AI | XGBoost
Education
N/A
Roles
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